activity
20182021
most citedLearning on Attribute-Missing Graphs

126 citations · 282 across the 33 of their papers we have counts for

collaborators

45 papers

cs.CV20211 cited

Collaborative Uncertainty in Multi-Agent Trajectory Forecasting

Bohan Tang, Yiqi Zhong, Ulrich Neumann +3

Uncertainty modeling is critical in trajectory forecasting systems for both interpretation and safety reasons. To better predict the future trajectories of multiple agents, recent…

cs.CV20211 cited

Spatio-Temporal Graph Complementary Scattering Networks

Zida Cheng, Siheng Chen, Ya Zhang

Spatio-temporal graph signal analysis has a significant impact on a wide range of applications, including hand/body pose action recognition. To achieve effective analysis, spatio-t…

cs.IR20213 cited

Click-through Rate Prediction with Auto-Quantized Contrastive Learning

Yujie Pan, Jiangchao Yao, Bo Han +3

Click-through rate (CTR) prediction becomes indispensable in ubiquitous web recommendation applications. Nevertheless, the current methods are struggling under the cold-start scena…

cs.CV20211 cited

A 3D Mesh-based Lifting-and-Projection Network for Human Pose Transfer

Jinxiang Liu, Yangheng Zhao, Siheng Chen +1

Human pose transfer has typically been modeled as a 2D image-to-image translation problem. This formulation ignores the human body shape prior in 3D space and inevitably causes imp…

cs.CV202176 cited

Multiscale Spatio-Temporal Graph Neural Networks for 3D Skeleton-Based Motion Prediction

Maosen Li, Siheng Chen, Yangheng Zhao +3

We propose a multiscale spatio-temporal graph neural network (MST-GNN) to predict the future 3D skeleton-based human poses in an action-category-agnostic manner. The core of MST-GN…

cs.CV2021

CaT: Weakly Supervised Object Detection with Category Transfer

Tianyue Cao, Lianyu Du, Xiaoyun Zhang +3

A large gap exists between fully-supervised object detection and weakly-supervised object detection. To narrow this gap, some methods consider knowledge transfer from additional fu…